Representative Bodies in the Age of AI

Curated on Posted on by Stefaan Verhulst

Report by POPVOX: “The report tracks current developments in the U.S. Congress and internationally, while assessing the prospects for future innovations. The report also serves as a primer for those in Congress on AI technologies and methods in an effort to promote responsible use and adoption. POPVOX endorses a considered, step-wise strategy for AI experimentation, underscoring the importance of capacity building, data stewardship, ethical frameworks, and insights gleaned from global precedents of AI in parliamentary functions. This ensures AI solutions are crafted with human discernment and supervision at their core.

Legislatures worldwide are progressively embracing AI tools such as machine learning, natural language processing, and computer vision to refine the precision, efficiency, and, to a small extent, the participatory aspects of their operations. The advent of generative AI platforms, such as ChatGPT, which excel in interpreting and organizing textual data, marks a transformative shift for the legislative process, inherently a task of converting rules into language.

While nations such as Brazil, India, Italy, and Estonia lead with applications ranging from the transcription and translation of parliamentary proceedings to enhanced bill drafting and sophisticated legislative record searches, the U.S. Congress is prudently venturing into the realm of Generative AI. The House and Senate have initiated AI working groups and secured licenses for platforms like ChatGPT. They have also issued guidance on responsible use…(More)”.

A tale of two cities: one real, one virtual

Curated on Posted on by Stefaan Verhulst

Joy Lo Dico in the Financial Times: “In recent years, digital city-building has become a legitimate part of urban planning. Barcelona, Cambridge and Helsinki are among a number of European cities exploring how copies of themselves could prove useful in making their built environments sharper, faster, cleaner and greener.

What exists in real life is being rendered a second time in the digital space: creating a library of the past, an eagle’s-eye view of the present and, potentially, a vision of the future.

One of the most striking projects has been happening in Ukraine, where technology company Skeiron has, since 2022, been mapping the country’s monuments, under threat from bombing.

The project #SaveUkrainianHeritage has recorded 60 buildings, from the St Sofia Cathedral in Kyiv and the Chernivtsi National University — both Unesco world heritage sites — to wooden churches across the country, something Skeiron’s co-founder Yurii Prepodobnyi mentions with pride. There are thousands of them. “Some are only 20 or 30 square metres,” he says. “But Ukrainian churches keep Ukrainian identity.”

With laser measurements, drone photography and photogrammetry — the art of stitching photographs together — Prepodobnyi and his team can produce highly detailed 3D models.

They have even managed to recreate the exterior of the Mariupol drama theatre, destroyed in the early days of the Ukraine war, after calling for photographs and drone footage.

Another project, in Pompeii, has been using similar digital techniques to capture the evolution of excavations into a 3D model. The Pompeii I. 14 Project, led by Tulane University and Indiana State University, takes the process of excavating buildings within one block of Pompeii, Insula 14, and turns it into a digital representation. Using laser measurements, iPad Pros, a consumer drone and handheld cameras, a space can be measured to within a couple of millimetres. What is relayed back along the stream is a visual record of how a room changes over thousands of years, as the debris, volcanic eruption and layers of life that went before are revealed…(More)”.

Experts in Government

Curated on Posted on by Stefaan Verhulst

Book by Donald F. Kettl: “From Caligula and the time of ancient Rome to the present, governments have relied on experts to manage public programs. But with that expertise has come power, and that power has long proven difficult to hold accountable. The tension between experts in the bureaucracy and the policy goals of elected officials, however, remains a point of often bitter tension. President Donald Trump labeled these experts as a ‘deep state’ seeking to resist the policies he believed he was elected to pursue—and he developed a policy scheme to make it far easier to fire experts he deemed insufficiently loyal. The age-old battles between expertise and accountability have come to a sharp point, and resolving these tensions requires a fresh look at the rule of law to shape the role of experts in governance…(More)”.

Facts over fiction: Why we must protect evidence-based knowledge if we value democracy

Curated on Posted on by Stefaan Verhulst

Article by Ben Feringa and Paul Nurse: “Central to human progress are three interconnected pillars. The first is pursuit of knowledge, a major component of which is the expansion of the frontiers of learning and understanding – something often achieved through science, driven by the innate curiosity of scientists.

The second pillar of progress is the need for stable democracies where people and ideas can mix freely. It is this free exchange of diverse perspectives that fuels the democratic process, ensuring policies are shaped by a multitude of voices and evidence, leading to informed decision-making that benefits all of society.

Such freedom of speech and expression also serves as the bedrock for scientific inquiry, allowing researchers to challenge prevailing notions without fear, fostering discovery, applications and innovation.

The third pillar is a fact-based worldview. While political parties might disagree on policy, for democracy to work well all of them should support and protect a perspective that is grounded in reliable facts, which are needed to generate reliable policies that can drive human progress….(More)”.

Privacy-Enhancing and Privacy-Preserving Technologies: Understanding the Role of PETs and PPTs in the Digital Age

Curated on Posted on by Stefaan Verhulst

Paper by the Centre for Information Policy Leadership: “The paper explores how organizations are approaching privacy-enhancing technologies (“PETs”) and how PETs can advance data protection principles, and provides examples of how specific types of PETs work. It also explores potential challenges to the use of PETs and possible solutions to those challenges.

CIPL emphasizes the enormous potential inherent in these technologies to mitigate privacy risks and support innovation, and recommends a number of steps to foster further development and adoption of PETs. In particular, CIPL calls for policymakers and regulators to incentivize the use of PETs through clearer guidance on key legal concepts that impact the use of PETs, and by adopting a pragmatic approach to the application of these concepts.

CIPL’s recommendations towards wider adoption are as follows:

  • Issue regulatory guidance and incentives regarding PETs: Official regulatory guidance addressing PETs in the context of specific legal obligations or concepts (such as anonymization) will incentivize greater investment in PETs.
  • Increase education and awareness about PETs: PET developers and providers need to show tangible evidence of the value of PETs and help policymakers, regulators and organizations understand how such technologies can facilitate responsible data use.
  • Develop industry standards for PETs: Industry standards would help facilitate interoperability for the use of PETs across jurisdictions and help codify best practices to support technical reliability to foster trust in these technologies.
  • Recognize PETs as a demonstrable element of accountability: PETs complement robust data privacy management programs and should be recognized as an element of organizational accountability…(More)”.

Testing the Assumptions of the Data Revolution

Curated on Posted on by Stefaan Verhulst

Report by TRENDS: “Ten years have passed since the release of A World that Counts and the formal adoption of the Sustainable Development Goals (SDGs). This seems an appropriate time for national governments and the global data community to reflect on where progress has been made so far. 

This report supports this objective in three ways: it evaluates the assumptions that underpin A World that Counts’ core hypothesis that the data revolution would lead to better outcomes across the 17 SDGs, it summarizes where and how we have made progress, and it identifies knowledge gaps related to each assumption. These knowledge gaps will serve as the foundation for the next phase of the SDSN TReNDS research program, guiding our exploration of emerging data-driven paradigms and their implications for the SDGs. By analyzing these assumptions, we can consider how SDSN TReNDs and other development actors might adapt their activities to a new set of circumstances in the final six years of the SDG commitments.

Given that the 2030 Agenda established a 15-year timeframe for SDG attainment, it is to be expected that some of A World that Counts’ key assumptions would fall short or require recalibration along the way. Unforeseen events such as the COVID-19 pandemic would inevitably shift global attention and priorities away from the targets set out in the SDG framework, at least temporarily…(More)”.

Tackling Today’s Data Dichotomy: Unveiling the Paradox of Abundant Supply and Restricted Access in the Quest for Social Equity

Curated on Posted on by Stefaan Verhulst

Article by Stefaan Verhulst: “…One of the ironies of this moment, however, is that an era of unprecedented supply is simultaneously an era of constricted access to data. Much of the data we generate is privately “owned,” hidden away in private or public sector silos, or otherwise inaccessible to those who are most likely to benefit from it or generate valuable insights. These restrictions on access are grafted onto existing socioeconomic inequalities, driven by broader patterns of exclusion and marginalization, and also exacerbating them. Critically, restricted or unequal access to data does not only harm individuals: it causes untold public harm by limiting the potential of data to address social ills. It also limits attempts to improve the output of AI both in terms of bias and trustworthiness.

In this paper, we outline two potential approaches that could help address—or at least mitigate—the harms: social licensing and a greater role for data stewards. While not comprehensive solutions, we believe that these represent two of the most promising avenues to introduce greater efficiencies into how data is used (and reused), and thus lead to more targeted, responsive, and responsible policymaking…(page 22-25)”.

Digital Self-Determination

Curated on Posted on by Stefaan Verhulst

New Website and Resource by the International Network on Digital Self Determination: “Digital Self-Determination seeks to empower individuals and communities to decide how their data is managed in ways that benefit themselves and society. Translating this principle into practice requires a multi-faceted examination from diverse perspectives and in distinct contexts.

Our network connects different actors from around the world to consider how to apply Digital Self-Determination in real-life settings to inform both theory and practice.

Our main objectives are the following:

  • Inform policy development;
  • Accelerate the creation of new DSD processes and technologies;
  • Estabilish new professions that can help implement DSD (such as data stewards);
  • Contribute to the regulatory and policy debate;
  • Raise awareness and build bridges between the public and private sector and data subjects…(More)”.

Ground Truths Are Human Constructions

Curated on Posted on by Stefaan Verhulst

Article by Florian Jaton: “Artificial intelligence algorithms are human-made, cultural constructs, something I saw first-hand as a scholar and technician embedded with AI teams for 30 months. Among the many concrete practices and materials these algorithms need in order to come into existence are sets of numerical values that enable machine learning. These referential repositories are often called “ground truths,” and when computer scientists construct or use these datasets to design new algorithms and attest to their efficiency, the process is called “ground-truthing.”

Understanding how ground-truthing works can reveal inherent limitations of algorithms—how they enable the spread of false information, pass biased judgments, or otherwise erode society’s agency—and this could also catalyze more thoughtful regulation. As long as ground-truthing remains clouded and abstract, society will struggle to prevent algorithms from causing harm and to optimize algorithms for the greater good.

Ground-truth datasets define AI algorithms’ fundamental goal of reliably predicting and generating a specific output—say, an image with requested specifications that resembles other input, such as web-crawled images. In other words, ground-truth datasets are deliberately constructed. As such, they, along with their resultant algorithms, are limited and arbitrary and bear the sociocultural fingerprints of the teams that made them…(More)”.

Generative AI for economic research: Use cases and implications for economists  

Curated on Posted on by Stefaan Verhulst

Paper by Anton Korinek: “…This article describes use cases of modern generative AI to interested economic researchers based on the author’s exploration of the space. The main emphasis is on LLMs, which are the type of generative AI that is currently most useful for research. I have categorized their use cases into six areas: ideation and feedback, writing, background research, data analysis, coding, and mathematical derivations. I provide general instructions for how to take advantage of each of these capabilities and demonstrate them using specific examples. Moreover, I classify the capabilities of the most commonly used LLMs from experimental to highly useful to provide an overview. My hope is that this paper will be a useful guide both for researchers starting to use generative AI and for expert users who are interested in new use cases beyond what they already have experience with to take advantage of the rapidly growing capabilities of LLMs. The online resources associated with this paper are available at the journal website and will provide semi-annual updates on the capabilities and use cases of the most advanced generative AI tools for economic research. In addition, they offer a guide on “How do I start?” as well as a page with “Useful Resources on Generative AI for Economists.”…(More)”